An Overview of Reviews on Telemedicine and Telehealth in Dementia Care: Mixed Methods Synthesis
Notice bibliographique
Résumé
Background: Population aging has intensified the global burden of dementia, creating significant challenges for patients, caregivers, and health care systems. While traditional in-person dementia care faces barriers, digital health technologies offer promising solutions to enhance accessibility, efficiency, and patient-centered care. However, evidence on applicability, safety, and effectiveness in dementia care remains fragmented, underscoring systematic evaluation. Objective: This study aims to assess the effectiveness, applicability, safety, and cost-efficiency of telemedicine technologies in dementia care, providing a comprehensive summary of evidence spanning clinical, psychological, socioeconomic, and operational impacts for persons living with dementia and their caregivers and assess alignment with the World Health Organization (WHO) Age-friendly Cities and Communities' Framework and Dementia Inclusive Society Framework. Methods: An overview of systematic and scoping reviews was conducted following a search in 5 databases (MEDLINE, Embase, Scopus, Epistemonikos, and Cochrane Database of Systematic Reviews), with a gray literature search on February 20, 2024. Eligible studies reported predefined outcomes related to telemedicine interventions for integrated dementia care, including effects on mental health, quality of life, physical activity, hospitalization, financial costs, safety, social isolation, and motor function. Screening and data extraction were performed by 10 reviewers. The findings were synthesized using the Thematic Analysis in Meta-Evidence (TAME) methodology, combining thematic and lexical analyses with single-proportion meta-analysis for comprehensive qualitative-quantitative synthesis. The methodological quality was assessed using the AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews), with GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative Research) for outcomes' confidence in evidence. Results: Ninety-one reviews provided evidence on the impact of telemedicine in dementia care. The most frequently reported outcomes were the effects of remote interventions on psychiatric and psychological well-being, particularly depression and anxiety (relative frequency of occurrence [RFO]=65%, 95% CI 54-75, moderate certainty of evidence). Fifty-seven studies highlighted the positive impact of telemedicine and telehealth on satisfaction and quality of life for persons living with dementia, caregivers, and health care providers (RFO=63%, 95% CI 52-73, moderate certainty of evidence). Remote technology-related interventions for reducing falls and managing behavioral symptoms were also frequently reported (RFO=33% 95% CI 23-44], moderate certainty of evidence). These interventions showed effectiveness in alleviating social isolation and loneliness (RFO=31%, 95% CI 22-41, moderate certainty of evidence). The methodological quality of the included reviews varied significantly, with the majority rated as low or critically low quality. Conclusions: Telemedicine and telehealth have been demonstrated to be effective and valuable tools in dementia care, offering significant benefits across psychological well-being, quality of life, and social impacts for persons living with dementia and their caregivers. This supports the adoption and implementation of telemedicine in dementia care, aligning with the strategies outlined in the United Nations Decade of Healthy Ageing (2021-2030).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,046 | 0,136 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,002 |
| Méta-épidémiologie (sens large) | 0,013 | 0,016 |
| Bibliométrie | 0,029 | 0,028 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».